Scalable policy assignment in an edge virtual bridging (EVB) environment

ABSTRACT

One embodiment includes obtaining virtual machine (VM) information for at least one VM. The VM information includes a VSI type identification (ID) associated with each VM. A policy discriminator (PD) is associated for each VSI type ID, where the PD represents scalable policy assignment. At least one rule and bandwidth filter information associated with a VSI type ID is retrieved from virtual station interface (VSI) database (DB) information and PD for each VSI type ID. The associated at least one rule and filter information is applied based on one of multiple PD types. The multiple PD types comprise a VM type and a virtual local area network (vLAN) type.

BACKGROUND

In EVB (Edge Virtual Bridging) environments, policies and attributes are specified for a particular virtual station interface (VSI) type identification (ID) (VSI Type ID). The policies are stored in a central configuration database called the VSI database (VSI DB). These policies could have actions, such as metering incoming packets, metering outgoing packets, deny and/or permit certain packets streams (filter) based on the nature of a virtual machine (VM). Ternary content addressable memory (TCAM) devices are used to implement rules and policies in hardware.

SUMMARY

Embodiments relate to scalable policy assignment in an edge virtual bridging (EVB) environment. One embodiment includes obtaining virtual machine (VM) information for at least one VM. The VM information includes a VSI type identification (ID) associated with each VM. A policy discriminator (PD) is associated for each VSI type ID, where the PD represents scalable policy assignment. At least one rule and bandwidth filter information associated with a VSI type ID is retrieved from virtual station interface (VSI) database (DB) information and PD for each VSI type ID. The associated at least one rule and filter information is applied based on one of multiple PD types. The multiple PD types comprise a VM type and a virtual local area network (vLAN) type.

These and other features, aspects and advantages of the present embodiments will become understood with reference to the following description, appended claims and accompanying figures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a cloud computing node according to an embodiment;

FIG. 2 depicts a cloud computing environment according to an embodiment;

FIG. 3 depicts abstraction model layers according to an embodiment;

FIG. 4 is a block diagram illustrating an EVB system for employing an embodiment;

FIG. 5 illustrates a block diagram of an EVB system utilizing scalable policy assignment, in accordance with an embodiment;

FIG. 6 illustrates a VSI-ID table format, in accordance with an embodiment;

FIG. 7 illustrates VSI DB table format, in accordance with an embodiment;

FIG. 8 illustrates VSI DB table format including a PD, in accordance with another embodiment; and

FIG. 9 is a block diagram showing a process for scalable policy assignment, in accordance with an embodiment.

DETAILED DESCRIPTION

It is understood in advance that although this disclosure includes a detailed description of cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, embodiments are capable of being implemented in conjunction with any other type of computing environment now known or later developed.

Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed, automatically without requiring human interaction with the service's provider.

Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time.

Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active consumer accounts). Resource usage can be monitored, controlled, and reported providing transparency for both the provider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer is to use the provider's applications running on a cloud infrastructure. The applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based email). The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited consumer-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application-hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds).

A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure comprising a network of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computing node is shown. Cloud computing node 10 is only one example of a suitable cloud computing node and is not intended to suggest any limitation as to the scope of use or functionality of embodiments described herein. Regardless, cloud computing node 10 is capable of being implemented and/or performing any of the functionality set forth hereinabove.

In cloud computing node 10, there is a computer system/server 12, which is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and/or configurations that may be suitable for use with computer system/server 12 include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. Computer system/server 12 may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10 is shown in the form of a general purpose computing device. The components of computer system/server 12 may include, but are not limited to, one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including system memory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer system/server 12, and it includes both volatile and non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and/or cache memory 32. Computer system/server 12 may further include other removable/non-removable, volatile/non-volatile computer system storage media. By way of example only, storage system 34 can be provided for reading from and writing to a non-removable, non-volatile magnetic media (not shown and typically called a “hard drive”). Although not shown, a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a “floppy disk”), and an optical disk drive for reading from or writing to a removable, non-volatile optical disk such as a CD-ROM, DVD-ROM, or other optical media can be provided. In such instances, each can be connected to bus 18 by one or more data media interfaces. As will be further depicted and described below, memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments.

The embodiments may be implemented as a computer readable signal medium, which may include a propagated data signal with computer readable program code embodied therein (e.g., in baseband or as part of a carrier wave). Such a propagated signal may take any of a variety of forms including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmitted using any appropriate medium including, but not limited to, wireless, wireline, optical fiber cable, radio-frequency (RF), etc., or any suitable combination of the foregoing.

Program/utility 40, having a set (at least one) of program modules 42, may be stored in memory 28 by way of example, and not limitation, as well as an operating system, one or more application programs, other program modules, and program data. Each of the operating systems, one or more application programs, other program modules, and program data or some combination thereof, may include an implementation of a networking environment. Program modules 42 generally carry out the functions and/or methodologies of embodiments as described herein.

Computer system/server 12 may also communicate with one or more external devices 14 such as a keyboard, a pointing device, a display 24, etc.; one or more devices that enable a consumer to interact with computer system/server 12; and/or any devices (e.g., network card, modem, etc.) that enable computer system/server 12 to communicate with one or more other computing devices. Such communication can occur via I/O interfaces 22. Still yet, computer system/server 12 can communicate with one or more networks such as a local area network (LAN), a general wide area network (WAN), and/or a public network (e.g., the Internet) via network adapter 20. As depicted, network adapter 20 communicates with the other components of computer system/server 12 via bus 18. It should be understood that although not shown, other hardware and/or software components could be used in conjunction with computer system/server 12. Examples include, but are not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 50 is depicted. As shown, cloud computing environment 50 comprises one or more cloud computing nodes 10 with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone 54A, desktop computer 54B, laptop computer 54C, and/or automobile computer system 54N may communicate. Nodes 10 may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as private, community, public, or hybrid clouds as described hereinabove, or a combination thereof. This allows cloud computing environment 50 to offer infrastructure, platforms, and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices 54A-N shown in FIG. 2 are intended to be illustrative only and that computing nodes 10 and cloud computing environment 50 can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers provided by cloud computing environment 50 (FIG. 2) is shown. It should be understood in advance that the components, layers, and functions shown in FIG. 3 are intended to be illustrative only and embodiments are not limited thereto. As depicted, the following layers and corresponding functions are provided:

Hardware and software layer 60 includes hardware and software components. Examples of hardware components include mainframes. In one example, IBM® zSeries® systems and RISC (Reduced Instruction Set Computer) architecture based servers. In one example, IBM pSeries® systems, IBM xSeries® systems, IBM BladeCenter® systems, storage devices, networks, and networking components. Examples of software components include network application server software. In one example, IBM WebSphere® application server software and database software. In one example, IBM DB2® database software. (IBM, zSeries, pSeries, xSeries, BladeCenter, WebSphere, and DB2 are trademarks of International Business Machines Corporation registered in many jurisdictions worldwide.)

Virtualization layer 62 provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers; virtual storage; virtual networks, including virtual private networks; virtual applications and operating systems; and virtual clients.

In one example, management layer 64 may provide the functions described below. Resource provisioning provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and pricing provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may comprise application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. Consumer portal provides access to the cloud computing environment for consumers and system administrators. Service level management provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment provides pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA.

Workloads layer 66 provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation; software development and lifecycle management; virtual classroom education delivery; data analytics processing; transaction processing; and scalable policy assignment. As mentioned above, all of the foregoing examples described with respect to FIG. 3 are illustrative only, and the embodiments are not limited to these examples.

It is understood all functions of the embodiments as described herein are typically performed by the scalable policy assignment system 500 (FIG. 5), which can be tangibly embodied as modules of program code 42 of program/utility 40 (FIG. 1). However, this need not be the case. Rather, the functionality recited herein could be carried out/implemented and/or enabled by any of the layers 60-66 shown in FIG. 3.

It is reiterated that although this disclosure includes a detailed description on cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, the embodiments are intended to be implemented with any type of clustered computing environment now known or later developed.

According to an embodiment, a scalable policy assignment process in an EVB environment implemented by the system 500 comprises fetching virtual machine (VM) information for one or more VMs from a virtual station interface (VSI) database (DB). The VM information includes a VSI type identification (ID) associated with each VM. A policy discriminator (PD) value is associated for each VSI type ID. A VSI DB table is generated with at least a portion of the VM information from the VSI DB and the PD for each VSI type ID. A message is received including virtual machine (VM) information for a created VM. One or more rules and bandwidth filter information associated with a VSI type ID are retrieved from the VSI DB table. The associated rules and filter information are applied based on the PD. The embodiments scale with policy associations with added VMs since the resources required (e.g., TCAMs) for the number of associated policies is proportional to the size of the VSI DB table including a PD.

FIG. 4 shows a block diagram illustrating an EVB system 100 for employing an embodiment. EVB system 100 includes a physical end station 110 that includes a hypervisor 111, VM 1 115 to VM N 115, virtual edge bridge (VEB) port 120. The VMs 1-N 115 include virtual interfaces 116 (e.g., virtual network interface card (VNIC), or VM NIC), applications, and operating systems. The VEB port 120 includes physical NICs 125 and communicates (e.g., ingress and egress) information (e.g., system traffic, network traffic, data, messages, etc.) with switch 130 (e.g., an adjacent bridge) through a VEB uplink 140 via switch ports 131.

The switch 130 may have one or more TCAMs 135 that are used for implementing EVB policies (e.g., metering rules, access rules, etc.) in hardware. The VSI DB 151 stores the EVB policies. The VM manager (e.g., server) 150 retrieves the EVB policies for association with a VM via the hypervisor 111, which transmits a VSI discovery protocol (VDP) associate message to the switch 130 for employing the policy rules using the TCAM 135. A VM 115 is associated with a particular VSI Type ID when it becomes active as part of the VDP protocol. Many of the VMs 1-N 115 may use the same VSI Type ID. In order to identify the VSI Type ID, it is essential that the TCAM rules include the VM 115 identification (media access control (MAC) address) to enforce/implement the correct policy. Therefore, the TCAM 115 rules may be replicated for each VM 115. Using the TCAM 135 mechanisms (e.g., look-ups, operations, etc.) does not scale since an increase in the number of TCAM rule replications for each VM 115 may require addition of more TCAMs 150 to the switch 130.

FIG. 5 illustrates a block diagram of an EVB system 500 utilizing scalable policy assignment, in accordance with an embodiment. In one embodiment, system 500 includes a policy assignment module 535 that generates a VSI-ID table 521 and a VSI DB table 522. In one example, the policy assignment module 535 fetches the VSI DB from the VM manager 150. The policy assignment module 535 uses the information (e.g., policies/rules (e.g., access control lists, etc.), transmission and receiving rates for different VM types, and any other pertinent information desired) from the VSI DB for generating the VSI DB table 522. In one embodiment, the VSI DB table 522 is stored in a memory in switch 130. In one example, the memory that the VSI DB table 522 is stored in may be any type of appropriate hardware memory device, and not necessarily a TCAM type of memory device.

In one embodiment, upon creation of a VM 115, the hypervisor 111 sends a VDP ASSOCIATE message to the switch 130. The ASSOCIATE message includes a value for the VSI Type ID, the source MAC address and virtual local area network (vLAN) ID (vLAN-ID) for the created VM 115. In one example, the VSI Type ID may be a number (e.g., 10, 20, 30, etc.). The VSI Type ID for a VSI determines what policies get applied to the server represented by that VSI at the VEB/VEPA bridge port. In one example, the policies are maintained by the VM Manager 150. In one embodiment, the switch 130 uses the value of the VSI Type ID for the created VM 115 to perform a lookup of the fetched VSI DB and validates the association request from the hypervisor 111.

In one embodiment, the policy assignment module 535 uses the value of the VSI Type ID, the vLAN-ID and source MAC address of the created VM 115 and generates the VSI-ID table 521. In one example, the VSI-ID table 521 provides a mapping between the VM's 115 source MAC addresses and the VSI Type ID. In one example, the VSI-ID table 521, once generated, is modified for all created VMs 115. In one embodiment, the switch performs a table look up (TLU) on the VSI-ID table 521 and outputs the source MAC address that is associated with vLAN-ID and VSI Type ID for the created VM 115. In one embodiment, the output from the VSI-ID table 521 is used as input to the VSI DB table 522.

In one embodiment, if the VSI Type ID is created for a first time, then the associated policies are entered (e.g., programmed, manually entered by an administrator, etc.) into the VSI DB table 522. In one example, the source MAC address of the created VM 115 and VSI Type ID are input into the VSI DB table 522 and the rule/policy information for the VM 115 based on the VSI Type ID is used to store the rule(s)/policy(ies) for the created VMs 115.

FIG. 6 illustrates a VSI-ID table format 600, in accordance with an embodiment. In one example, the format 600 for the VSI-ID table 521 includes fields for a source MAC address 610, vLAN-ID 620, and VSI Type ID 630. In one example, the source MAC address 610 may comprise bits for representing the source MAC address 610. In one example, the vLAN-ID 620 may comprise bits for representing a value (e.g., a number, or other representation) for the vLAN that the VM 115 is associated with. In one example, the VSI-ID-TYPE 630 may comprise bits for representing a value (e.g., a number, or other representation) for the VSI type that the VM 115 is associated with.

FIG. 7 illustrates a VSI DB table format 700, in accordance with an embodiment. In one example, the format 700 for the VSI DB table 522 includes fields for a VSI Type ID 710, vLAN-ID 720, access control lists (ACLs) 730 (e.g., policies/rules), transmission rate 740, and receiving rate 750. In one example, the VSI Type ID 710 may comprise bits for representing the VSI type associated with a particular VM 115. In one example, the vLAN-ID 720 may comprise bits for representing a value (e.g., a number, or other representation) for the vLAN that the VM 115 is associated with. In one example, the ACLs 730 may comprise bits for representing rules/policies for the VSI type and vLAN type that the VM 115 is associated with. In one example, the transmission rate 740 and receiving rate 750 comprise bits representing the transmission and reception rates for the VM 115 associated with a VSI Type ID 710 and vLAN-ID 720.

In one embodiment, the scalability for managing policies in the system 500 is readily seen by the following example. For one example, consider twenty (20) VMs 115 are associated with a VSI Type ID 10, and ten (10) VMs 115 are associated with a VSI Type ID 20. Without using the system 50 including the policy assignment module 535, VSI-ID table 521 and VSI DB table 522, a system, such as system 100, would need to create 50 rules/policies instances (i.e., replicated rules). That is, since the VSI Type ID 710 for VSI-TYPE 10 is associated with two ACLs 730 (e.g., ac11 and ac12), and there are 20 of these VMs 115, there would be forty (40) instances of the rules/policies for the VMs 115 associated with VSI-TYPE 10. For the VSI-TYPE 20, since there are 10 VMs 115 and only one ACL, there would be 10 instances of the rules/policies for the VMs 115 associated with VSI type 10.

In one embodiment, using the system 500 with the VSI DB format 700 for a VSI table 522, there are two ACLs 730 (e.g., two rules/policies) that need to be entered in the VSI DB 522, instead of 50 entries/instances that would be required by system 100. Therefore, the number of bits required to implement the VSI-ID table 521 is much less than ACL entries that would be stored in a TCAM 135 of system 100.

FIG. 8 illustrates a VSI DB table format 800, in accordance with an embodiment. In one embodiment, the format 800 for the VSI DB table 522 includes fields for a VSI Type ID 710, vLAN-ID 720, filters 830 (e.g., policies/rules), transmission rate 840, receiving rate 850 and policy discriminator 860. In one example, the filters 830 may comprise bits for representing rules/policies for the VSI type and vLAN type that the VM 115 is associated with. In one example, the transmission rate 840 and receiving rate 850 comprise bits representing the associated transmission and reception rates for the VM 115 based on the PD 860. In one embodiment, the PD 860 serves to scope the policy as the PD 860 allows implementation of policies based on VMs or based on vLANs. Using vLANs allows for a coarse policy that is shared across all VMs. In one example, a smaller set of vLANs (e.g., 10, 12, etc.) may exist in system 500 as compared to a number of VMs (e.g., 2000 or more). In one example, if the associated PD 860 is of type VM, then finer-grained policies may be applied that are more VM specific. The two types of policies (i.e., VM and vLAN) may co-exist with each other. In one embodiment, scaling of VMs 115 occurs without increasing hardware requirements for TCAMs 135.

In one embodiment, the scalability for assignment of policies in the system 500 using the PD 860 is readily seen by the following comparison. For one example, consider five (5) VMs 115 that are associated with a VSI Type ID 10 and three (3) VMs 115 that are associated with a VSI Type ID 20. In this example, 10 TCAM 435 instances are required to be stored for implementing filters for VSI Type ID 10, 5 TCAM 435 instances are required to be stored for implementing <txrate 1>, 5 TCAM 435 instances are required to be stored for implementing <rxrate 1>, 3 TCAM 435 instances are required to be stored for implementing filters for VSI Type ID 20, 3 TCAM 435 instances are required to be stored for implementing <txrate 2>, and 3 TCAM 435 instances are required to be stored for implementing <rxrate 2>. That is, 29 total TCAM 435 rules would be required to be implemented as TCAM 435 rules.

In one example, using the VSI DB 800 format for system 500, for the PD 860 for a vLAN (e.g., a PD value of “LN”) for VSI Type ID 10, only 2 TCAM 435 instances are required for implementation of the filters (e.g., <rule 1> and <rule 2>), only 1 TCAM 435 instance is required for implementation of <txrate 1>, and only 1 TCAM 435 instance is required for implementation of <rxrate 1>. For the PD 860 for a VM (e.g., a PD value “VM”) for VSI Type ID 20, 3 TCAM 435 instances are required to be stored for implementing the filter (e.g., <rule 3>) for VSI Type ID 20, 3 TCAM 435 instances are required to be stored for implementing <txrate 2>, and 3 TCAM 435 instances are required to be stored for implementing <rxrate 2>. That is, a total of 13 TCAM 435 instances are required by using the PD 860 of VSI DB table format 800 for system 500. Therefore, in this example it is readily seen that for small number of VMs 115 associated with multiple filters/rules 830 for VSI-ID-Type 10, only 13 instances of TCAM 435 rule implementations are required instead of 29 instances without using a PD 860.

In one embodiment, using the system 500 with the VSI DB format 800 for a VSI DB table 522, there are two Filters/Rules 830 (e.g., two policies) that need to be entered in the VSI DB 522, instead of 10 entries/instances that would be required by system 100 or system 500 with using the VSI DB table format 700. Therefore, the number of bits required to implement the VSI DB table 522 is much less than Filter/Rule instances that would be stored in a TCAM 135 of system 100.

In the above example, for VSI Type ID 10, the PD 860 value of “LN” has been associated. This association allows all VMs 115 that are bound to LN 100 to share the same filters/rules 830 <rule 1>, <rule 2>, the same transmission rate 840 <txrate 1>, and the same receiving rate 850 <rxrate 1>. In contrast, VSI Type ID 20 does not benefit the implementation savings as only one filter/rule <rule 1> is associated with the PD 860. In this case, each VM 115 consumes hardware resources (e.g., TCAM 135) for installing <rule 3>, <txrate2> and <rxrate2>.

In one embodiment, the switch 130 fetches the VSI DB 151 from the VM manager 150 (e.g., server). Upon a VM 115 being created, the hypervisor 111 sends a VDP ASSOCIATE message to the switch 130. The ASSOCIATE message contains the value of the VSI Type ID, source MAC address, and vLAN-ID for that VM 115. The policy assignment module 535 of switch 130 uses the value of the VSI Type ID to look up the PD 860 of VSI DB 522 using the VSI DB format 800 and implements the following:

If the associated PD 860 is equal to a selected “LN,” the policy assignment module 535 checks if rules (e.g., access lists (ACLs) and bandwidth filters already exist for that LN. If TRUE, do nothing. Otherwise, program the rules and bandwidth filters for that LN. If the associated PD 860 is equal to a selected “VM,” the policy assignment module 535 programs the rule and bandwidth filters for that VM. Subsequently, when a data frame from the VM arrives at the switch port, the hardware TCAM 135 applies the rules and filters that match. For the TCAM 135, the match key is either the vLAN ID, or the tuple (src-mac-address, vLAN ID), depending on the granularity that has been chosen.

FIG. 9 illustrates a flowchart of an example process for scalable policy assignment 900, according to one embodiment. In process block 910, VSI DB information is fetched, for example, by the switch 130 of system 500 shown in FIG. 5. In process block 920, a PD (e.g., PD 860) is associated for a VM (e.g., VM 115). In process block 930, a VSI DB table (e.g., VSI DB table 522) including a field for PDs 860 is created. In process block 940, message is received including VM information for a created VM. In process block 950, rules/policies (e.g., filters/rules 830) and bandwidth filter information are retrieved from the VSI DB table based on the associated PD. In process block 970, the rules/policies and filter bandwidth information that were retrieved from the VSI DB table are applied based on the associated PD. Therefore, process 900 provides for scaling of rules associated with different associated PDs 860 of VMs 115.

The system 500 may include one or more source programs, executable programs (object code), scripts, or any other entity comprising a set of computer program instructions to be performed. When the system 500 includes a source program, then the program is usually translated via a compiler, assembler, interpreter, or the like, which may or may not be included within a storage device. These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

In the context of this document, a “computer-readable medium” can be any means that can store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer readable medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, propagation medium, or other physical device or means that can contain or store a computer program for use by or in connection with a computer related system or method.

As will be appreciated by one skilled in the art, aspects of the embodiments may be embodied as a system, method or computer program product. Accordingly, aspects of the present embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present embodiments may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon.

In the context of this document, a “computer-readable medium” can be any means that can store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer readable medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, propagation medium, or other physical device or means that can contain or store a computer program for use by or in connection with a computer related system or method.

More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic or optical), a random access memory (RAM) (electronic), a read-only memory (ROM) (electronic), an erasable programmable read-only memory (EPROM, EEPROM, or Flash memory) (electronic), an optical fiber (optical), and a portable compact disc memory (CDROM, CD R/W) (optical). Note that the computer-readable medium could even be paper or another suitable medium, upon which the program is printed or punched (as in paper tape, punched cards, etc.), as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.

A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

In one embodiment, where the system 500 is implemented in hardware, the system 500 can be implemented with any one or a combination of the following technologies, which are each well known in the art: a discrete logic circuit(s) having logic gates for implementing logic functions upon data signals, an application specific integrated circuit (ASIC) having appropriate combinational logic gates, a programmable gate array(s) (PGA), a field programmable gate array (FPGA), etc.

Aspects of the present embodiments are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the embodiments. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

It should be emphasized that the above-described embodiments, particularly, any “preferred” embodiments, are merely possible examples of implementations, merely set forth for a clear understanding of the principles of the embodiments.

Many variations and modifications may be made to the above-described embodiment(s) without departing substantially from the spirit and principles of the embodiments. All such modifications and variations are intended to be included herein within the scope of this disclosure and the present embodiments and protected by the following claims. 

What is claimed is:
 1. A method comprising: fetching virtual machine (VM) information for one or more VMs from a virtual station interface (VSI) database (DB), wherein the VM information includes, for each VM, an associated VSI type identification (ID), and each VSI type ID is associated with a policy discriminator (PD) value; generating a VSI DB table based on a portion of the VM information and each PD value associated with each VSI type ID; retrieving at least one rule and bandwidth filter information associated with a VSI type ID from the VSI DB table; and applying the at least one rule and bandwidth filter information based on one of multiple PD values, wherein the multiple PD values represent different types of policies, thereby enabling scaling of VMs without increasing hardware requirements for ternary content addressable memories (TCAMs).
 2. The method of claim 1, wherein the different types of policies include a first policy for a virtual local area network (vLAN) and a second policy for a VM.
 3. The method of claim 2, wherein the first policy is a coarse policy that is shared across all VMs, and the second policy is a fine-grained policy that is VM specific.
 4. The method of claim 2, wherein the first policy and the second policy co-exist with each other without an increased number of TCAM instances.
 5. The method of claim 1, further comprising: receiving a message including additional VM information for a created VM; wherein the at least one rule and bandwidth filter information are applied further based on the additional VM information.
 6. A system comprising: at least one processor; and a non-transitory processor-readable memory device storing instructions that when executed by the at least one processor causes the at least one processor to perform operations including: fetching virtual machine (VM) information for one or more VMs from a virtual station interface (VSI) database (DB), wherein the VM information includes, for each VM, an associated VSI type identification (ID), and each VSI type ID is associated with a policy discriminator (PD) value; generating a VSI DB table based on a portion of the VM information and each PD value associated with each VSI type ID; retrieving at least one rule and bandwidth filter information associated with a VSI type ID from the VSI DB table; and applying the at least one rule and bandwidth filter information based on one of multiple PD values, wherein the multiple PD values represent different types of policies, thereby enabling scaling of VMs without increasing hardware requirements for ternary content addressable memories (TCAMs).
 7. The system of claim 6, wherein the different types of policies include a first policy for a virtual local area network (vLAN) and a second policy for a VM.
 8. The system of claim 7, wherein the first policy is a coarse policy that is shared across all VMs, and the second policy is a fine-grained policy that is VM specific.
 9. The system of claim 7, wherein the first policy and the second policy co-exist with each other without an increased number of TCAM instances.
 10. The system of claim 6, wherein the operations further comprise: receiving a message including additional VM information for a created VM; wherein the at least one rule and bandwidth filter information are applied further based on the additional VM information.
 11. A non-transitory computer-readable medium storing instructions that, when executed by at least one processor of a machine, cause the machine to perform operations comprising: fetching virtual machine (VM) information for one or more VMs from a virtual station interface (VSI) database (DB), wherein the VM information includes, for each VM, an associated VSI type identification (ID), and each VSI type ID is associated with a policy discriminator (PD) value; generating a VSI DB table based on a portion of the VM information and each PD value associated with each VSI type ID; retrieving at least one rule and bandwidth filter information associated with a VSI type ID from the VSI DB table; and applying the at least one rule and bandwidth filter information based on one of multiple PD values, wherein the multiple PD values represent different types of policies, thereby enabling scaling of VMs without increasing hardware requirements for ternary content addressable memories (TCAMs).
 12. The computer program product of claim 11, wherein the different types of policies include a first policy for a virtual local area network (vLAN) and a second policy for a VM.
 13. The computer program product of claim 12, wherein the first policy is a coarse policy that is shared across all VMs, and the second policy is a fine-grained policy that is VM specific.
 14. The computer program product of claim 12, wherein the first policy and the second policy co-exist with each other without an increased number of TCAM instances.
 15. The computer program product of claim 11, wherein the operations further comprise: receiving a message including additional VM information for a created VM; wherein the at least one rule and bandwidth filter information are applied further based on the additional VM information. 